Voice Recognition Algorithm Research Articles

The Development of a Speech Recognition Software Application Using HMM, ANN and LPC Models to Minimize Error

The purpose of this application is to develop speech recognition software applications and test it. The developed speech recognition system for human language solves for processing the voice input and answering the queries of the user. This system begins with an introduction to Speech Recognition Technology then it explains how it works, and the level of accuracy that can be expected. The system is considered for the possible applications of speech technology, including every single task related with the action of the human voice. In this sense, the application fields can vary from speech production, storage, transmission and recognition processes. This research pertains to discuss the theories and models on speech communication and more importantly the use of technology for speech recognition. Several authors’ views are discussed but a great emphasis is given to the Hidden Markov Models (HMM), Artificial Neural Network (ANN) and Liner Predictive Coding (LPC). The aim of the research is to test these models and outline voice recognition algorithms which are important in improving the voice recognition performance. The application is tested with speakers used to represent different tones, emotions and lengths in metres as a sample of relationships methodology, the reports the system permits are used in the results analysis.

The Improved DTW Voice Recognition Algorithm

Due to reduce the amount of DTW algorithm and improve the recognition rate. Through using the traditional DTW algorithm for analysis and research, putting forward a kind of local path constraints and regional restrictions combined with improved DTW algorithm. Through the experiment, using the improved DTW algorithm can reduce the calculate operations and improve the recognition rate.

Based on Spectral Analysis of Voice Controllable Surveillance System Using Normalized Mean Square Error

In the article the authors present an algorithm to recognize the human voice, whose operation is based on the analysis of spectra using a measure of the quality of NMSE (normalized mean square error) used to compare digital images. Proposed in the article of voice recognition algorithm has been applied practically to voice control a visual surveillance system.

Improving Older Adults' Experience with Interactive Voice Response Systems

Interactive voice response (IVR) systems use computer-based voice recognition and software algorithms to conduct human/computer interactions. In recent years, there has been a proliferation of IVR applications in business and healthcare. The available evidence suggests that older people have negative attitudes towards IVR and experience significant difficulties using these systems. The goal of this project was to identify areas of difficulties in IVR use by older people and propose strategies for improvement. During two focus groups, we examined older people's perceptions of IVR systems and the most common difficulties experienced by seniors in interacting with these systems. We also recorded their suggestions for improvement of IVR. Frequency and chi square analyses were performed on the focus groups data. Some of the difficulties reported by participants in this study were congruent with previous findings, but we also uncovered some additional problems, such as frustration for not being able to reach an operator, being asked to wait too long on hold, being unable to recover from mistakes, and an absence of shortcuts in the systems. In addition, significant number of participants indicated that they prefer a system that adjusts to them automatically as opposed to a system that allows for adjustment. Generally, our findings suggest that the poor acceptability of IVR systems by older people could be improved by designing IVR algorithms that detect difficulties during an ongoing IVR exchange and direct people to different algorithms adapted for each person.

Feature based RDWT watermarking for multimodal biometric system

This paper presents a 3-level RDWT biometric watermarking algorithm to embed the voice biometric MFC coefficients in a color face image of the same individual for increased robustness, security and accuracy. Phase congruency model is used to compute the embedding locations which preserves the facial features from being watermarked and ensures that the face recognition accuracy is not compromised. The proposed watermarking algorithm uses adaptive user-specific watermarking parameters for improved performance. Using face, voice and multimodal recognition algorithms, and statistical evaluation, we show that the proposed RDWT watermarking algorithm is robust to different frequency and geometric attacks, and provides the multimodal biometric verification accuracy of 94%.

Two technologies vie for recognition in speech market

Improvements to voice-recognition algorithms and greater computing power have changed speech technology from an approach with limited uses to an increasingly important part of many applications. As this process has unfolded, developers have searched for an open standard, rather than proprietary development and runtime environments, that would let them easily and quickly add speech input/output capabilities to applications that function across platforms, said Inderpal Singh Mumick, founder and CEO of Kirusa, a wireless platform developer. Two principal approaches have resulted from this search: VoiceXML and SALT (speech application language tags).

Simultaneous voice recognition and verification to allow access to telephone network services

The present invention describes a system and method for enabling a caller to obtain access to services via a telephone network by entering a spoken password having a plurality of digits. Preferably, the method includes the steps of: (1) prompting the caller to speak the password beginning with a first digit and ending with a last digit thereof, (2) recognizing each spoken digit of the password using a speaker-independent voice recognition algorithm, (3) following entry of the last digit of the password, determining whether the password is valid, and (4) if the password is valid, verifying the caller's identity using a voice verification algorithm.

The current status of the development of an active noise control microphone

This paper describes the current status of the development of a simple unitary active microphone that provides superior noise cancellation. The microphone, based on active noise control principles, is small and does not require an independent sample of the ambient noise. At the same time, there is no requirement for locating the microphone near the speaker's mouth, as required with conventional passive noise canceling microphones. Instead, the microphone under development can be placed several feet, or more, from the speaker, since superior performance of the new microphone can still be realized. The microphone element can discriminate between the voice and noise even at a distance without voice recognition algorithms, and all kinds of noises, including random noise, can be canceled. A simple electronic control unit can be used to produce commercial systems.

Ergonomic Aspects for Improving Recognition Performance of Voice Input Systems

Present voice input systems have a recognition rate less than 100%. Beside the quality of the voice recognition algorithms some ergonomie factors relating to the speaker, the vocabulary and the environmental noise determine the recognition rate. In a series of experiments 7 parameters (speaker training, long-term speech consistency, system training, speaker sex, vocabulary phonetics, -size, background noise) were tested in a simple word input task. The experiments were performed with different vocabularies (mostly the ICAO alphabet) and with one or both of the voice input systems Threshold T600 and SpeechLab 20A. The results are reported and discussed in the context of the literature.